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At least 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Continuous assessment of metabolic activity of mitochondria using resonance Raman microspectroscopy

Dysfunctional mitochondrial activity can lead to a variety of different diseases. As such, there exists a need to quantify changes in mitochondria function as it relates to these specific diseased states. Here, we present the use of resonance Raman (RR) spectroscopy as a tool to determine changes in isolated mitochondrial activity. RR spectroscopy, using 532 nm as the excitation source, specifically provides information on the reduction and oxidation (RedOx) state of cytochrome c, which is determined by the activity of protein complexes in the electron transport chain. In this model, injection of the substrate succinate into the mitochondrial sample is used to drive the electron transport chain, which causes a subsequent change in cytochrome c RedOx state. This change in RedOx state is tracked by RR spectroscopy. We report this tool gives real-time information on the rise and fall of the amount of reduced cytochrome c within the mitochondrial sample, providing a method for rapid assessment of mitochondrial metabolism that has broad applications in both basic science and medical research.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A stochastic biomass blending problem in decentralized supply chains

Blending biomass materials of different physical or chemical properties provides an opportunity to adjust the quality of the feedstock to meet the specifications of the conversion platform. We propose a model which identifies the right mix of biomass to optimize the performance of the thermochemical conversion process at the mini-mum cost. This is a chance-constraint programming (CCP) model which takes into account the stochastic nature of biomass quality. The proposed CCP model ensures that process requirements, which are impacted by physical and chemical properties of biomass, are met most of the time. We consider two problem settings, a centralized and a decentralized supply chain. We propose a mixed-integer linear program to model the blending problem in the centralized setting and a bilevel program to model the blending problem in the decentralized setting. We use the sample average approximation method to approximate the chance constraints, and propose solution algorithms to solve this approximation. We develop a case study for South Carolina using data provided by the Billion Ton Study. Based on our results, the blends identified consist mainly of pine and softwood residues. The blends identified and the suppliers selected by both models are different. The cost of the centralized supply chain is 2%–6% lower. The implications of these results are twofold. First, these results could lead to improved collaborations in the supply chain. Second, these results provide an estimate of the approximation error from assuming centralized decision making in the supply chain.

09 BIOMASS FUELS↗
DOE OSTI2023

Establishing the accuracy of position–specific carbon isotope analysis of propane by GC–pyrolysis–GC–IRMS

Rationale: Position-specific (PS) δ 13 C values of propane have proven their ability to provide valuable information on the evolution history of natural gases. Two major approaches to measure PS δ 13 C values of propane are isotopic 13 C nuclear magnetic resonance (NMR) and gas chromatography-pyrolysis-gas chromatography-isotope ratio mass spectrometry (GC-Py-GC-IRMS). Measurement accuracy of the isotopic 13 C NMR has been verified, but the requirements of large sample size and long experimental time limit its applications. GC-Py-GC-IRMS is a more versatile method with a small sample size, but its accuracy has not been demonstrated. Methods: We measured the PS δ 13 C values of propane from nine natural gases using both 13 C NMR and GC-Py-GC-IRMS, then evaluated the accuracy of the GC-Py-GC-IRMS method. Results: The results show that large carbon isotope fractionations occurred for both terminal and central carbons within propane during pyrolysis. The isotope fractionations during the pyrolysis are reproducible at optimum conditions, but vary between the two GC-Py-GC-IRMS systems tested, affected by experimental conditions (e.g., pyrolysis temperature, flow rate, and reactor conditions). Conclusions: It is necessary to evaluate and calibrate each GC-Py-GC-IRMS system using propane gases with accurately determined PS δ 13 C values. Finally, this study also highlights a need for PS isotope standards for propane and other molecules (e.g., butane and acetic acid).

03 NATURAL GAS↗
DOE OSTI2023

Visualization and efficient generation of constrained high-dimensional theoretical parameter spaces

We describe a set of novel methods for efficiently sampling high-dimensional parameter spaces of physical theories defined at high energies, but constrained by experimental measurements made at lower energies. Often, theoretical models such as supersymmetry are defined by many parameters, $\mathcal{O}$(10 – 100), expressed at high energies, while relevant experimental constraints are often defined at much lower energies, preventing them from directly ruling out portions of the space. Instead, the low-energy constraints define a complex, potentially non-contiguous subspace of the theory parameters. Naive scanning of the theory space for points which satisfy the low-energy constraints is hopelessly inefficient due to the high dimensionality, and the inverse problem is considered intractable. As a result, many theoretical spaces remain under-explored. We introduce a class of modified generative autoencoders, which attack this problem by mapping the high-dimensional parameter space to a structured low-dimensional latent space, allowing for easy visualization and efficient generation of theory points which satisfy experimental constraints. An extension without dimensional compression, which focuses on limiting potential information loss, is also introduced.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Optimization models for integrated biorefinery operations

Variations of physical and chemical characteristics of biomass lead to an uneven flow of biomass in a biorefinery, which reduces equipment utilization and increases operational costs. Uncertainty of biomass supply and high processing costs increase the risk of investing in the US’s cellulosic biofuel industry. We propose a stochastic programming model to streamline processes within a biorefinery. A chance constraint models system’s reliability requirement that the reactor is operating at a high utilization rate given uncertain biomass moisture content, particle size distribution, and equipment failure. The model identifies operating conditions of equipment and inventory level to maintain a continuous flow of biomass to the reactor. Furthermore, the sample average approximation method approximates the chance constraint and a bisection search-based heuristic solves this approximation. A case study is developed using real-life data collected at Idaho National Laboratory’s biomass processing facility. An extensive computational analysis indicates that sequencing of biomass bales based on moisture level, increasing storage capacity, and managing particle size distribution, increases utilization of the reactor and reduces operational costs.

09 BIOMASS FUELS↗
DOE OSTI2021

Measurement of High-temperature Thermophysical Properties of Bulk and Coatings Using Modulated Photothermal Radiometry

This paper presents the development of instrumentation for the measurement of high-temperature thermal conductivity of bulk and coatings using a modulated photothermal radiometry (MPR) method, where a sample is heated by an intensity-modulated laser to probe into different layers of the sample. While MPR has been previously established, most of the previous studies only focus on the measurement at room temperature. The MPR has not been well studied for measurements of bulk and coating materials at high temperatures, which are increasingly important for a multitude of applications, such as materials used in the concentrating solar power (CSP) plants and the nuclear reactors. MPR is a non-contact technique that utilizes the intrinsic thermal emission from the specimens for thermometry, which is favorable for measurements at high temperatures in harsh environment. The authors designed and utilized a sample holder suitable for high temperature measurement up to 973 K with good temperature uniformity within the sample. The high-temperature MPR setup was validated by measuring bulk materials with known thermal conductivity. The setup and technique were then extended to the measurement of black solar-absorbing coatings of 10 to 50 μm thick on various substrates by modulating the frequency of the laser heating beam and the thermal penetration depth. Here, the studies showed that thermal conductivities of typical solar-absorbing coatings are 0.4 ~ 0.8 W m -1 K -1 , indicating a possibly large temperature drop within the coating under high solar irradiation flux, such as over 1000-sun for central solar towers in CSP plants.

14 SOLAR ENERGY↗
DOE OSTI2025

Correlation of optical properties with particle size, morphology, and polymorph of fine- and nano-particle formulations of titanium dioxide powders

Titanium dioxide (TiO 2 ) particulates are known to exhibit different visible and infrared optical properties compared to the bulk material, showing strong dependence on particle size, crystal structure, and morphology. In this study, the optical properties, sizes, and morphologies of TiO 2 particles from two different sources (nano and fine powders) having a) nominally different particle sizes and b) various crystal polymorph mixture fractions are compared using a combination of single particle mass spectrometry, optical spectroscopies, and aerosol characterization methods. The nano sample was found to be largely particles of the anatase polymorph (88% by mass), while the fine sample was found to consist largely of rutile particles (95% by mass). Two distinct particle morphologies (fractal and compact) were found in each powder sample and could be identified and separated in-situ based on particle aerodynamic properties. The attenuation of near-infrared, visible and ultraviolet light by TiO 2 particles shows strong dependence on particle morphology. Furthermore, while the fine particles were found to have larger near-infrared (675–800 nm) extinction coefficients by mass than the nanoparticles, the reverse was true in the ultraviolet and visible regions (370–675 nm). However, for polydisperse particles with different sizes and shapes, the optical behaviors are not straightforward to directly correlate to a combination of physical parameters.

Lockwood, Schuyler P. [Pacific Northwest National ↗
DOE OSTI2020

Multiscale formulation of frictional contact mechanics at the pore scale

Direct numerical simulation (DNS) yields the highest fidelity predictions of mechanical deformation at the pore scale, but is prohibitively expensive for analyzing large or many samples. Discrete element methods (DEM) are an efficient alternative, but are limited to granular media and incapable of estimating or controlling prediction errors. We present a pore-level multiscale method (PLMM) that approximates DNS efficiently and with controllable accuracy. We focus on the linear elastic response of a consolidated geologic porous medium with arbitrary microstructure, heterogeneous mineralogy, containing cracks or defects. PLMM decomposes the solid phase into non-overlapping subdomains, on which local basis functions are constructed. The bases are then coupled with a global interface problem that accounts for slip or stick contact conditions between the subdomains. PLMM produces an initial, but accurate, approximation to DNS that can be iteratively improved. It is amenable to parallelism and allows for different mesh, models, and physics in each subdomain. An algebraic interpretation of PLMM as a preconditioner is also presented to allow non-intrusive implementation into existing solvers. Lastly, this work extends previous developments of PLMM in fluid dynamics to solid mechanics and enables future extensions towards modeling coupled flow and mechanics problems.

42 ENGINEERING↗
DOE OSTI2022

GenMod: A generative modeling approach for spectral representation of PDEs with random inputs

Here, we propose a method for quantifying uncertainty in high-dimensional PDE systems with random parameters, where the number of solution evaluations is small. Parametric PDE solutions are often approximated using a spectral decomposition based on polynomial chaos expansions. For the class of systems we consider (i.e., high dimensional with limited solution evaluations) the coefficients are given by an underdetermined linear system in a regression formulation. This implies additional assumptions, such as sparsity of the coefficient vector, are needed to approximate the solution. Here, we present an approach where we assume the coefficients are close to the range of a generative model that maps from a low to a high dimensional space of coefficients. Our approach is inspired be recent work examining how generative models can be used for compressed sensing in systems with random Gaussian measurement matrices. Using results from PDE theory on coefficient decay rates, we construct an explicit generative model that predicts the polynomial chaos coefficient magnitudes. The algorithm we developed to find the coefficients, which we call GenMod, is composed of two main steps. First, we predict the coefficient signs using Orthogonal Matching Pursuit. Then, we assume the coefficients are within a sparse deviation from the range of a sign-adjusted generative model. This allows us to find the coefficients by solving a nonconvex optimization problem, over the input space of the generative model and the space of sparse vectors. We obtain theoretical recovery results for a Lipschitz continuous generative model and for a more specific generative model, based on coefficient decay rate bounds. We examine three high-dimensional problems and show that, for all three examples, the generative model approach outperforms sparsity promoting methods at small sample sizes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Evaluation of the critical behavior near ferromagnetic to paramagnetic phase transition in CrTe 1-x Se x alloys: An experimental study

For this study, we used the conventional solid-state reaction method to prepare stoichiometric samples of CrTe 1-x Se x , where 0 ≤ x ≤ 0.10, and investigated the structural and critical behavior of the prepared samples. Room temperature powder X-ray diffraction, along with Rietveld refinement, revealed the emergence of the NiAs structure with P6 3 /mmc (194) space group with increasing Se substitution. The high-temperature linear fit to inverse of the dc-susceptibility versus temperature for the mother sample resulted in an effective moment of 3.65μ B Cr with Curie-Weiss temperature near 335K, which is slightly higher than the Tc of ~332K obtained from the inflection point of magnetization versus temperature. Magnetization isotherms were employed to investigate the critical behavior of ferromagnetic CrTe 1-x Se x with 0.0 ≤ x ≤ 0.10 near their Curie temperatures (Tc). The magnetic behavior near Tc was found to follow 3D mean-field critical exponents with a second-order phase transition in all samples investigated. We fine-tuned the critical exponents (β, γ, and δ) using a combination of an iteration technique, the Kouvel-Fisher method, and modified Arrott plots. All samples follow a mean field behavior, with Tc ranging from 298 to 340K. The acquired values exhibit self-consistency, as indicated by the results from the Widom scaling relation. Furthermore, the magnetization isotherms exhibit a universal scaling behavior, providing additional credence to the calculated critical exponents.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Ion Dissociation Dynamics in an Aqueous Premelting Layer

Using molecular dynamics simulations and methods of importance sampling, we study the thermodynamics and dynamics of sodium chloride in the aqueous premelting layer formed spontaneously at the interface between ice and its vapor. We uncover a hierarchy of time scales that characterize the relaxation dynamics of this system, spanning the picoseconds of ionic motion to the tens or hundreds of nanoseconds associated with fluctuations of the liquid-crystal interface in their presence. We find that ions distort both local interfaces, incurring restoring forces that result in the ions preferentially residing in the middle of the layer. While ion pair dissociation is thermodynamically favorable, these structural and dynamic effects cause its rate to vary by over an order of magnitude through the layer, with a maximum rate significantly depressed from the corresponding bulk value. The solvation environment of ions in the premelting layer is distinct from that in a bulk liquid, being dominated by slow reorganization of water molecules and a water structure intermediate between ice and its melt.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Parallelized Screening of Characterized and DFT-Modeled Bimetallic Colloidal Cocatalysts for Photocatalytic Hydrogen Evolution

Using a newly designed and developed parallelized photoreactor and colorimetric detection method, a large sampling of bimetallic co-catalysts (Pd/Sn, Pd/Mo, Pd/Ru, Pd/Pb, Pd/Ni, Ni/Sn, Mo/Sn and Pt/Sn) for photocatalytic water reduction have been tested in this work. Of these co-catalysts, the combination of palladium and tin showed the highest synergistic behavior and peak hydrogen gas production at a low relative fraction of palladium. The resulting Pd/Sn bimetallic co-catalysts were characterized using high-angle annular dark-field (HAADF) and scanning transmission electron microscopy energy dispersive X-ray spectroscopy (STEM-EDS), and specifically, investigation of the palladium/tin mixture indicated that palladium and tin elements reside within the same particle. The experimental catalytic activity for the palladium/tin mixture was compared to density functional theory-derived energy values associated with the adsorption of hydrogen onto a surface. This comparison demonstrated that the typical peak found in electrochemical Sabatier volcano plots at ΔG H* = ~0 eV was replicated in the experimental photocatalytic system with a peak activity observed at ΔG H* = -0.036 eV. Computational confirmation of the results expressed here demonstrates the efficacy of colorimetric detection of hydrogen in parallel and presents a model for increasingly rapid catalyst screening.

08 HYDROGEN↗
DOE OSTI2024

The Arctic Plant Aboveground Biomass Synthesis Dataset

Plant biomass is a fundamental ecosystem attribute that is sensitive to rapid climatic changes occurring in the Arctic. Nevertheless, measuring plant biomass in the Arctic is logistically challenging and resource intensive. Lack of accessible field data hinders efforts to understand the amount, composition, distribution, and changes in plant biomass in these northern ecosystems. Here, we present The Arctic plant aboveground biomass synthesis dataset, which includes field measurements of lichen, bryophyte, herb, shrub, and/or tree aboveground biomass (g m -2 ) on 2,327 sample plots from 636 field sites in seven countries. We created the synthesis dataset by assembling and harmonizing 32 individual datasets. Aboveground biomass was primarily quantified by harvesting sample plots during mid- to late-summer, though tree and often tall shrub biomass were quantified using surveys and allometric models. Each biomass measurement is associated with metadata including sample date, location, method, data source, and other information. This unique dataset can be leveraged to monitor, map, and model plant biomass across the rapidly warming Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A global dataset of terrestrial biological nitrogen fixation

Biological nitrogen fixation (BNF) is the main natural source of new nitrogen inputs in terrestrial ecosystems, supporting terrestrial productivity, carbon uptake, and other Earth system processes. We assembled a comprehensive global dataset of field measurements of BNF in all major N-fixing niches across natural terrestrial biomes derived from the analysis of 376 BNF studies. The dataset comprises 32 variables, including site location, biome type, N-fixing niche, sampling year, quantification method, BNF rate (kg N ha −1 y −1 ), the percentage of nitrogen derived from the atmosphere (%N dfa ), N fixer or N-fixing substrate abundance, BNF rate per unit of N fixer abundance, and species identity. Overall, the dataset combines 1,207 BNF rates for trees, shrubs, herbs, soil, leaf litter, woody litter, dead wood, mosses, lichens, and biocrusts, 152 herb %N dfa values, 1,005 measurements of N fixer or N-fixing substrate abundance, and 762 BNF rates per unit of N fixer abundance for a total of 424 species across 66 countries. This dataset facilitates synthesis, meta-analysis, upscaling, and model benchmarking of BNF fluxes at multiple spatial scales.

Reis Ely, Carla R. [Oregon State Univ., Corvallis,↗
DOE OSTI2023

A simple soil mass correction for a more accurate determination of soil carbon stock changes

Abstract Agricultural soils can act as a sink for large quantities of soil organic carbon (SOC) but can also be sources of carbon to the atmosphere. The international standard for assessing SOC stock and measuring stock change stipulates fixed depth sampling to at least 30 cm. The tendency of bulk density (BD) to decrease with decreasing disturbance and increasing SOC concentration and the assumption of constant SOC and BD within this depth profile promotes error in the estimates of SOC stock. A hypothetical but realistic change in BD from 1.5 to 1.1 g cm −3 from successive fixed depth sampling to 30 cm underestimates SOC stock change by 17%. Significant effort has been made to evaluate and reduce this fixed depth error by using the equivalent soil mass (ESM) approach, but with limited adoption. We evaluate the error in SOC stock assessment and change generated from fixed depth measurements over time relative to the ESM approach and propose a correction that can be readily adopted under current sampling and analytical methods. Our approach provides a more accurate estimate of SOC stock accumulation or loss that will help incentivize management practice changes that reduce the environmental impacts of agriculture and further legitimize the accounting practices used by the emerging carbon market and organizations that have pledged to reduce their supply chain greenhouse gas (GHG) footprints.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

The need for multicomponent dust attenuation in modeling nebular emission: Constraints from SDSS-IV MaNGA

A fundamental assumption adopted in nearly every extragalactic study that analyzes optical emission lines is that the attenuation of different emission lines can be described by a single attenuation curve, scaled by a single reddening parameter, usually E(B - V). Here we show this assumption fails in many cases with important implications for derived results. We developed a new method to measure the differential nebular attenuation among three kinds of transitions: the Balmer lines of hydrogen; high-ionization transitions (> 13.6 eV) including [Ne III], [O III], and [S III]; and low-ionization transitions (≲13.6 eV) including [O II], [N II], and [S II]. This method bins the observed data in a multidimensional space spanned by attenuation-insensitive line ratios. Within each small bin, the variations in nebular parameters such as the metallicity and ionization parameter are negligible compared to the variation in the nebular attenuation. This allowed us to measure the nebular attenuation using both forbidden lines and Balmer lines. We applied this method to a sample of 2.4 million star-forming (SF) spaxels from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey. We found that the attenuation of high ionization lines and Balmer lines can be well described by a single Fitzpatrick (1999, PASP, 111, 63) extinction curve with R V = 3.1. However, no single attenuation curve can simultaneously account for these transitions and the derived attenuation of low-ionization lines. This strongly suggests that different lines have different effective attenuations, likely because spectroscopy at hundreds of parsecs to kiloparsecs of resolution mixes multiple physical regions that exhibit different intrinsic line ratios and different levels of attenuation. As a result, the assumption that different lines follow the same attenuation curve breaks down. Using a single attenuation curve determined by Balmer lines to correct attenuation-sensitive forbidden line ratios could bias the nebular parameters derived by 0.06–0.25 dex at A V = 1, depending on the details of the dust attenuation model. Observations of a statistically large sample of H II regions with high spatial resolutions and large spectral coverage are vital for improved modeling and deriving accurate corrections for this effect.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

3D scanning and 3D printing AlSi10Mg single crystal mounts for neutron scattering

Here, we present methods to quantify sample shapes and generate sample mounts as motivated by the needs of neutron scattering experiments. The 3D sample scanning was performed using photogrammetry and laser scanning, and a comparison is made between the two techniques. The aluminum alloy AlSi10Mg is shown to have favorable properties for many types of mounts used in neutron scattering. Parts were first prototyped with 3D plastic printers, and then, 3D AlSi10Mg prints were made. The final additively manufactured part holds the sample with more points of contact than is possible with traditional manufacturing. The goodness of fit between the mount and sample was measured by x-ray tomography.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Analysis techniques for blob properties from gas puff imaging data

Filamentary structures, also known as blobs, are a prominent feature of turbulence and transport at the edge of magnetically confined plasmas. They cause cross-field particle and energy transport and are, therefore, of interest in tokamak physics and, more generally, nuclear fusion research. Several experimental techniques have been developed to study their properties. Among these, measurements are routinely performed with stationary probes, passive imaging, and, in more recent years, Gas Puff Imaging (GPI). In this work, we present different analysis techniques developed and used on 2D data from the suite of GPI diagnostics in the Tokamak à Configuration Variable, featuring different temporal and spatial resolutions. Although specifically developed to be used on GPI data, these techniques can be employed to analyze 2D turbulence data presenting intermittent, coherent structures. We focus on size, velocity, and appearance frequency evaluation with, among other methods, conditional averaging sampling, individual structure tracking, and a recently developed machine learning algorithm. We describe in detail the implementation of these techniques, compare them against each other, and comment on the scenarios to which these techniques are best applied and on the requirements that the data must fulfill in order to yield meaningful results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗